Unmanned wave glider heading model identification and control by artificial fish swarm algorithm

We introduce the artificial fish swarm algorithm for heading motion model identification and control parameter optimization problems for the“Ocean Rambler”unmanned wave glider(UWG).First,under certain assumptions,the rigid-flexible multi-body system of the UWG was simplified as a rigid system composed of“thruster+float body”,based on which a planar motion model of the UWG was established.Second,we obtained the model parameters using an empirical method combined with parameter identification,which means that some parameters were estimated by the empirical method.In view of the specificity and importance of the heading control,heading model parameters were identified through the artificial fish swarm algorithm based on tank test data,so that we could take full advantage of the limited trial data to factually describe the dynamic characteristics of the system.Based on the established heading motion model,parameters of the heading S-surface controller were optimized using the artificial fish swarm algorithm.Heading motion comparison and maritime control experiments of the“Ocean Rambler”UWG were completed.Tank test results show high precision of heading motion prediction including heading angle and yawing angular velocity.The UWG shows good control performance in tank tests and sea trials.The efficiency of the proposed method is verified.

西南地区壳斗科物种丰富度和特有性分布格局模拟及其环境解释

如何准确地模拟物种宏观丰富度格局和特有性中心是生物多样性保护工作的重点,也是生物地理学的热点话题。西南地区是我国壳斗科植物最丰富的地区之一,但物种多样性格局及环境驱动机制尚不清楚。本研究基于西南地区161种壳斗科植物7258个分布点位数据,利用点格局法和物种分布模型两种方式构建了物种丰富度、加权特有性指数和校正加权特有性指数的分布格局,并采用空间自回归模型(SAR)分析上述3个多样性指数与环境因子间的关系。总体上看,物种分布模型模拟的3个指数在空间上比点格局法更为连续,但数值高低分布情况具有相似性:两种方式模拟的物种丰富度高值区主要分布在滇南边缘、桂北部和桂西南部地区(62~89种);加权特有性指数最大值集中在滇南和桂西地区(1.77~5.02);藏东南、秦岭-大巴山、桂西南部和滇东南地区具有最高的校正加权特有性指数(0.07~0.17)。SAR模型结果显示:最干月降雨量、温度季节性变化标准差、海拔变幅和土壤有机碳含量对物种丰富度的影响均显著,最干月降雨量、温度季节性变化标准差、潜在蒸散量和海拔变幅对加权特有性有着显著影响,温度季节性变化标准差、最干月降雨量、历史温度变化、增强型植被指数变异系数和海拔变幅对校正加权特有性的影响显著;SAR模型对物种丰富度、特有性指数和加权特有性指数的拟合效果(R2=0.857、0.733、0.593)分别优于普通线性模型(R2=0.689、0.425、0.422)。综上,水分可获得性、气候季节性、生境异质性、历史气候变化和土壤状况是制约西南地区壳斗科丰富度和特有性分布的最重要因素。滇南、滇东南、桂西南、桂西、秦岭-大巴山以及藏东南地区是壳斗科物种丰富度中心或特有性中心,应受到重点关注和保护。